AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions Arvind Hulgeri and S. Sudarshan   View Paper (PDF)   Return to Query Optimization (Session C2) Abstract The cost of a query plan depends on many pa- rameters, such as predicate selectivities and available memory, whose values may not be known at optimization time. Parametric query optimization (PQO) optimizes a query into a number of candidate plans, each opti- mal for some region of the parameter space. We propose a heuristic solution for the PQO problem for the case when the cost functions may be nonlinear in the given parameters. This solution is minimally intrusive in the sense that an existing query optimizer can be used with minor modi cations. We have im- plemented the heuristic and the results of the tests on the TPCD benchmark indicate that the heuristic is very effective. The minimal intrusiveness, generality in terms of cost func- tions and number of parameters and good per- formance (up to 4 parameters) indicate that our solution is of significant practical impor- tance. ©2004 Association for Computing Machinery